INTRODUCTION

The emergence of MR fingerprinting (MRF) technology has made it possible to reliably and accurately quantify T₁ and T₂ relaxation times. This advancement has paved the way for numerous studies aiming to utilize changes in relaxation times as potential indicators of diseases, equipping clinicians with non-invasive tools to gain insights into tissue pathophysiology^1-3. However, patients undergoing medical interventions, such as surgeries resulting in the implantation of metal devices like aneurysm clips, plates, screws, and dental orthodontic appliances, are common in various medical conditions. While these individuals can safely undergo 3T MRI examinations, and conventional morphological imaging diagnosis may not be significantly affected^{4, 5}, their influence on quantitative imaging remains unclear.
Consequently, we conducted a series of experiments using a standardized quantitative MRI phantom (ISMRM/NIST)⁶. Our study aimed to investigate how cranial bone plates, cranial screws, aneurysm clips, and metal molding strips of medical mask (representing outdated dental orthodontic metal braces and dentures) affect the quantification of T₁ and T₂ relaxation times using MRF at 3T. To provide a comprehensive analysis, we also collected data from conventional T₁ and T₂ mapping sequences.

METHODS

Cranial bone plates, cranial screws, aneurysm clips, and metal molding strips of the mask were each secured to the exterior of the phantom using medical elastic bandages. Subsequently, the phantoms underwent two rounds of scanning, which included MRF and traditional T₁ and T₂ mapping imaging (Mapit), across three 3T MRI scanners (all of which were MAGNETOM Vida, Siemens Healthineers, Erlangen, Germany). To maintain consistency, we had the phantoms situated in the scanning room beforehand, minimizing any temperature fluctuations during the six experiments.
The results from the two quantitative measurements were averaged, and we assessed whether the presence of medical implants significantly influenced the quantitative T₁ and T₂ values as well as the size of the affected area when compared to a control groups without any metal implants.

RESULTS

Our study revealed that aneurysm clips made from TiAl6V4 did not introduce artifacts or numerical anomalies in MRF images. However, compared to the control group without any metal implant placed (Figure 1), cranial bone plates and screws made from TiAl6Nb7 produced artifacts within a 5~7 mm range and numerical anomalies within 3~5 mm range (Figure 2 A, D). Furthermore, the Galvanized steel material used for nose clipping of the medical mask generated conspicuous artifacts within a 57~70 mm range and completely abnormal values within an 87~99 cm range (Figure 2 B, D). While in terms of accuracy/robustness, with the metal implant were existed, MRF provides more accurate quantitative results of T₁ and T₂ than Mapit technology (Figure 2 C).
Practical application has demonstrated that metal implants located within the maxillofacial region could potentially influence quantitative imaging of brain tissues. For patients who have undergone cranial surgeries, local brain tissues may experience alterations within the affected area of the metal implant.

DISCUSSION

The assessment of the impact of metal implants on imaging is crucial for postoperative follow-ups or MRI scans involving patients with metal implants, especially in the context of quantitative imaging. Our systematic investigation focused on the influence of common craniofacial metallic implants on relaxation time quantification. Based on our phantom study, we concluded that aneurysm clips made from TiAl6V4 had no significant impact on relaxation time quantification in MRF. In contrast, cranial bone plates and screws composed of TiAl6Nb7 exhibited mild signal abnormalities within a 3~5 mm range, while metal molding strips of the mask made from Galvanized steel led to obvious signal abnormalities within an 87~99 mm range. Traditional mapping techniques appear to be more sensitive to metal implants, resulting in more significant signal abnormalities in terms of both extent and severity.
Consequently, during clinical examinations or scientific research, it is essential to exercise caution when process the data from patient involving metal implants. Regions affected by the implant should be excluded from the region of interest to ensure the accuracy of results. Furthermore, ongoing research is investigating the development of quantitative MRI sequences that are less susceptible to the interference of metal implants and even multi-parameter quantitative imaging techniques⁷. These advancements are expected to enhanced the accuracy of quantitative MRI examination.

CONCLUSION

Our study offers empirical data on the influence of metal implants on 3T magnetic resonance relaxation time quantitative imaging. We need to carefully assess the presence of metal implants to ensure the accuracy of quantitative MRI results.

Acknowledgements

No acknowledgement found.

References

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